Storage Grid Vehicle Routing With Time-Interval Route Locking
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Solution Overview
Problem
Existing automated storage and retrieval systems face inefficiencies in routing and rerouting container handling vehicles due to the need for complete route planning, which can lead to delays and limited route alternatives, especially in dynamically changing environments.
Innovation Solution
A method that calculates routes on the fly, allowing partial route locking for a set time interval, enabling frequent rerouting and increased route alternatives by using multi-agent pathfinding algorithms while avoiding the need for complete route recalculation, allowing vehicles to adapt to traffic changes and new tasks without stopping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complete route planning is performed for container handling vehicles, then route reliability is improved, but route calculation time increases and system adaptability decreases
Solution Approach 1:
The patent segments the route planning process into discrete time intervals, where routes are planned and locked for specific durations rather than computing complete end-to-end routes upfront. This allows the system to maintain reliable locked routes while reducing overall calculation time by processing routes in manageable segments over time.
Solution Approach 2:
The system dynamically adjusts route planning by allowing routes to be locked for specific time intervals and automatically releasing them for recalculation when time expires or changes occur. This dynamic approach enables the system to maintain reliability during locked periods while adapting quickly to new conditions, reducing the need for complete recalculation.
2Reliability
If complete route planning is performed for container handling vehicles, then route reliability is improved, but system adaptability to dynamic changes worsens
Solution Approach 1:
The system implements periodic route planning where routes are locked for predetermined time intervals and then released for recalculation. This periodic mechanism maintains route reliability during locked periods while providing regular opportunities to adapt to dynamic changes, balancing both requirements effectively.
Solution Approach 2:
By making the route locking duration adjustable and time-bound rather than fixed for the entire journey, the system becomes dynamically adaptable. Routes can be locked long enough to ensure reliability for critical segments while remaining flexible enough to be recalculated when system conditions change, improving overall adaptability.
3Adaptability or versatility
If frequent rerouting is enabled with partial route locking, then system adaptability improves and journey time decreases, but route planning complexity increases
Solution Approach 1:
The patent simplifies the complexity of frequent rerouting by segmenting routes into lockable time intervals rather than requiring complex real-time recalculation of entire routes. This segmentation allows frequent, manageable rerouting decisions at interval boundaries without overwhelming computational complexity.
4Productivity
If partial route locking for set time intervals is implemented, then productivity improves through reduced calculation time, but route reliability may worsen due to frequent rerouting
Solution Approach 1:
The system maintains reliability despite frequent rerouting by implementing periodic locking where routes are secured for specific time intervals. This periodic locking ensures that once a route is calculated, it remains reliable and unchanged for its locked duration, preventing the reliability deterioration that could result from constant rerouting while still achieving productivity gains through efficient time-bound planning.
Data Source
AI summary
An automated storage and retrieval system includes a framework structure forming a three-dimensional storage grid structure for storing the storage containers in storage columns. The framework structure includes a grid-based rail system arranged above the storage columns with the rail system providing available routes for the container handling vehicles handling and transferring the storage containers to and from the storage columns. Each container handling vehicle includes a first set of wheels configured to move the vehicle along a first lateral direction of the grid-based rail system and a second set of wheels configured to move the vehicle along a second lateral direction of the grid-based rail system. The second direction is perpendicular to the first direction. The movements of the container handling vehicles are controlled by a control system that determines which tasks are to be done by specified container handling vehicles, destination locations for performing the tasks, and which routes the container handling vehicles are to travel on the rail system. A method for routing and rerouting of container handling vehicles handling storage containers in the automated storage and retrieval system comprises the control system performing: (a) running a multi-agent pathfinding algorithm, MAPF, in the control system for establishing and assigning routes on the rail system for the container handling vehicles from their current locations to assigned tasks at destination locations; (b) determining how far the container handling vehicles can travel on a first part of the assigned routes within a set time interval, the first part being shorter than the assigned routes to the destinations; (c) locking the first parts of the assigned routes that the container handling vehicles can travel within the set time interval, wherein the locked first parts of the routes cannot be changed and are excluded from consideration of available routes during running the MAPF algorithm; (d) extending the locked first parts of the assigned route for a container handling vehicle which is given priority; and (e) instructing the container handling vehicles to move from their current locations to an end location on the assigned locked routes; and (f) repeating steps (a) to (f).